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| DATE | 2004-12-01 |
| FROM | Ruben Safir
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| SUBJECT | Subject: [hangout] GNU/Linux gains in data warehousing
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Data Warehousing Infrastructure: Linux Clusters for the Enterprise
Article published in DM Review
Magazine
December 2004 Issue
By Shankar Radhakrishnan
Gone are the days when your business could justify a data warehouse
based on ROI alone.
Traditionally, businesses needed a large initial investment to build a
data warehouse that satisfied the requirements of a growing enterprise
and generated the desired return on investment (ROI). As long as the
projected ROI covered the cost, not even the capital-intensive
proprietary hardware systems or large SMP servers were considered
significant. But recently, a tough economy has forced businesses to look
for additional value from their technology investments. That's why today
many IT and business managers are focusing on total cost of ownership
(TCO) rather than solely on ROI when it comes to defining what makes a
data warehouse project successful.
Linux clusters are emerging as the de facto choice for providing
enterprise-level scalability, performance and availability for data
warehousing solutions at a low cost.
The Pillars of Data Warehousing
The pillars of a successful data warehouse infrastructure are
performance, availability, scalability and cost. A crack in any one of
those pillars can put your data warehousing project in jeopardy.
Performance must be good enough to handle the throughput of large
numbers of concurrent, typically very complex, queries on top of a
rapidly growing data warehouse - without forcing users to waste hours
waiting for queries to execute. Availability must be 24x7 - regardless
of hardware or software failures - to avoid costly downtime and to meet
the service level objectives that users expect from their transaction
processing systems. Scalability is critical to any business that wants
to grow, but the uncertainty of the business environment makes it
difficult for managers to predict data warehouse requirements. They
should implement a flexible infrastructure that can quickly and easily
expand on demand.
Businesses want all of this at a fraction of the cost of expensive
proprietary infrastructure solutions, and they don't want to have to
justify large upfront investments for IT capacity that may not be
utilized immediately. Additional costs such as managing infrastructure,
accessing skilled resources and training should also be kept low.
Emergence of Enterprise Linux Clusters
Linux clusters can help businesses build a high performance, reliable
and scalable enterprise data warehouse infrastructure capable of scaling
to handle tens of terabytes of data at a dramatically lower cost than
that of proprietary solutions. Businesses of all sizes can benefit from
the many advantages of an enterprise data warehouse built on low-cost
Linux clusters.
There is hardly any need to explain the price/performance benefits of
Linux systems to IT managers, as it is highly likely that they're
already benefiting from Web, e-mail and file servers running on Linux in
their data centers. Linux customers enjoy the low total-cost advantages
of commodity hardware, such as competitive pricing, elimination of
proprietary extensions and transferable skills.
While IT managers were initially reluctant to deploy mission-critical
applications on Linux, those doubts have become a concern of the past
with the availability of enterprise versions of Linux from leading
vendors such as Red Hat and SUSE, and the support of Linux from major
enterprise software and hardware vendors such as Oracle, HP and IBM. To
support data warehouses, major improvements have been made to the Linux
kernel with regard to I/O throughput, memory utilization, scalability,
reliability, manageability and clustering through contributions from
these vendors. A data warehouse can take advantage of Linux clusters to
deliver the high performance, scalability, availability and low TCO
demanded by today's businesses.
Scalability Requirements
The key requirement for scalability is that the data warehouse must be
able to support larger volumes of data and more users by adding
additional hardware - without degrading performance. While proprietary
servers often support large numbers of CPUs (up to 60 or 72 CPUs per
server), a single commodity server supports a much smaller number of
CPUs (up to 8 CPUs). Therefore, commodity servers running Linux require
clustering to scale.
Clustered data warehouses can be broadly categorized into two types:
shared-nothing architectures, where each server accesses its own set of
disks and database files, and shared-everything architectures, where
each server can access all available storage. The basic premise behind
both cluster architectures is that scalability is achieved by permitting
data warehouses to grow with the addition of new servers to the existing
cluster.
Instead of "forklift" upgrades where the incremental cost of scaling to
a larger server can be very expensive, businesses can scale their data
warehouse by incrementally adding low-cost servers to their cluster as
demand grows. When increasing the size of an existing shared-nothing
cluster, new storage and servers are typically purchased at the same
time, and the existing database is reorganized to be distributed across
the old and new servers. Shared-disk architectures offer more
flexibility for growth, because servers and storage may be added when
the need for either arises without requiring database reorganization.
Enter the Grid
Interesting new capabilities are being introduced to Linux clusters in
the area of grid computing. A grid is essentially an enterprise-wide
cluster supporting multiple applications. A key characteristic of a grid
is provisioning, which allows businesses to add or remove CPUs as needed
- even while the application is running. Database vendors are starting
to support such capabilities. Databases can recognize new CPUs instantly
and dynamically allocate workload to new nodes based on business
priorities.
For example, an enterprise grid could automatically and dynamically add
CPUs to its data warehouse during a heavy overnight load process or
during periods of high query activity and remove those CPUs from the
data warehouse when they are no longer needed. Thus, provisioning will
require a shared-everything architecture. One of the promises made by
Linux running on commodity servers is that it makes grid architectures a
reality. The widespread availability of inexpensive industry-standard
Linux servers enables companies to run entire enterprises on large
grids. With some of the largest-scale Linux clusters in commercial grid
computing, data warehouse applications are leading the adoption of grid
computing.
Performance
Performance of any system is driven primarily by its CPU power and I/O
bandwidth. Commodity hardware systems, based on Intel architecture CPUs,
deliver industry-leading price/performance. It is no longer necessary
for businesses to spend millions on large proprietary data warehouse
servers when superior complex query performance can be achieved on a
much smaller budget using the flexibility of a Linux cluster. The TPC-H
benchmark, a standard benchmark measuring complex database query
performance (www.tpc.org), demonstrates this. A recent TPC-H benchmark
on Linux clusters achieved an impressive performance of 22,387.9
QphH-at-3000GB with an unmatched price/performance of $93/QphH-at-3000GB.1
Linux clusters have met the performance requirements of even the most
demanding businesses.
High Availability
Data warehousing has evolved from systems primarily used for strategic
planning into mission-critical applications used in daily operations. A
failure in the data warehouse is no longer just an inconvenience to
internal analysts. It has the potential to cause a costly inability to
serve customers and manage internal operations. A data warehouse based
on Linux can eliminate concerns about downtime and ensure 24x7
availability.
Clustering, the key enabler for scalability, is also a crucial component
for availability. A single commodity Linux server may have a shorter
mean-time-to-failure than a high-priced proprietary server; however, a
cluster of Linux servers providing failover capabilities delivers 24x7
enterprise availability. Shared-everything architectures are ideal for
high-availability because all nodes equally share access to all disks.
When a server in a cluster becomes unavailable, the remaining servers
continue to function uninterrupted, automatically picking up the
workload of the failed server. Also, the linear scalability model of
Linux clusters eliminates guesswork regarding the actual power added or
removed when a new CPU is added or removed. For example, if one node
fails in an 8-node cluster, then the data warehouse system performs at
7/8th the capacity of the full cluster.
TCO Advantage
The overriding factor for building a data warehouse on a Linux cluster
is a significantly lower TCO. Cost is the driving consideration for
every data warehouse implementation on Linux today. The benefits accrued
from using Linux clusters are in the utilization of commodity,
Intel-based servers. Moreover, further cost benefits are recognized when
these servers are matched with low-cost storage solutions. An early
adopter of an 8-node Linux cluster cited almost a 14x cost savings
compared to their proprietary shared-nothing data warehouse solution.
The benefits of low-cost storage are even more dramatic, with that same
customer noting a 19x cost savings on the storage alone.
Additionally, replacing a failed server is cheap, fast and easy. The
"pay as you grow" model of a scale-out approach enables businesses to
avoid nearly instant obsolescence inherent in high-end systems and take
advantage of Moore's law. Buying a server two years down the line offers
hardware that is more powerful at lower cost. This model allows
businesses to align their IT capital spending with their business
growth. Business managers can do well by investing savings in their core
business.
Linux Clusters are Right for Data Warehousing
A data warehousing infrastructure built on a Linux cluster provides
enterprise-level scalability, performance and availability at an
unbeatable low cost. With Linux clusters, organizations can efficiently
scale-out operations and make their data warehouses available 24x7.
Businesses can avoid investing in excess computing power at premium
prices and benefit from the lower cost of open-standards-based
computing. Finally, customers can obtain all the benefits of a Linux
cluster data warehouse without incurring excessive management overhead.
The TCO of a Linux cluster-based data warehousing infrastructure is
significantly lower than the same solution implemented on a large SMP
box or a proprietary shared-nothing cluster. With all of these benefits,
it is not surprising that enterprise data warehouses built on low-cost
Linux clusters have emerged as an attractive alternative to proprietary
data warehouse solutions.
References:
1. Eight-node HP ProLiant DL740 Cluster each with 4 Intel Xeon MP 3.0
GHz processors running Red Hat Enterprise Linux AS 3 and Oracle Database
10g with Real Application Clusters available March 02, 2004.
________________________________________________________________________
Shankar Radhakrishnan is a senior product manager of Data Warehousing
Products at Oracle Corporation. He has been with Oracle for more than
seven years, most recently as the manager for CRM Interaction Center
Product Development and currently with Data Warehousing. He can be
contacted at Shankar.Radhakrishnan-at-oracle.com.
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